{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "74f0a34c-cc26-4c67-b7ea-5bcd8bed14aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==================================================\n",
      "GBDT产品定价模型分析\n",
      "==================================================\n",
      "\n",
      "数据基本信息：\n",
      "数据形状: (1000, 5)\n",
      "\n",
      "前5行数据：\n",
      "    页数   类别  彩印   纸张  价格\n",
      "0  207  技术类   0  双胶纸  60\n",
      "1  210  技术类   0  双胶纸  62\n",
      "2  206  技术类   0  双胶纸  62\n",
      "3  218  技术类   0  双胶纸  64\n",
      "4  209  技术类   0  双胶纸  60\n",
      "\n",
      "各列数据类型：\n",
      "页数     int64\n",
      "类别    object\n",
      "彩印     int64\n",
      "纸张    object\n",
      "价格     int64\n",
      "dtype: object\n",
      "\n",
      "数据描述性统计：\n",
      "                页数           彩印           价格\n",
      "count  1000.000000  1000.000000  1000.000000\n",
      "mean    293.848000     0.352000    63.905000\n",
      "std      99.523313     0.477833    20.029007\n",
      "min      61.000000     0.000000    20.000000\n",
      "25%     232.000000     0.000000    50.000000\n",
      "50%     292.000000     0.000000    62.000000\n",
      "75%     363.250000     1.000000    80.000000\n",
      "max     571.000000     1.000000   114.000000\n",
      "\n",
      "类别分布：\n",
      "类别\n",
      "技术类    336\n",
      "教辅类    333\n",
      "办公类    331\n",
      "Name: count, dtype: int64\n",
      "\n",
      "彩印分布：\n",
      "彩印\n",
      "0    648\n",
      "1    352\n",
      "Name: count, dtype: int64\n",
      "\n",
      "纸张分布：\n",
      "纸张\n",
      "双胶纸    615\n",
      "铜版纸    196\n",
      "书写纸    189\n",
      "Name: count, dtype: int64\n",
      "\n",
      "类别编码映射：\n",
      "  办公类 -> 0\n",
      "  技术类 -> 1\n",
      "  教辅类 -> 2\n",
      "\n",
      "纸张编码映射：\n",
      "  书写纸 -> 0\n",
      "  双胶纸 -> 1\n",
      "  铜版纸 -> 2\n",
      "\n",
      "特征变量形状: (1000, 4)\n",
      "目标变量形状: (1000,)\n",
      "\n",
      "训练集大小: (800, 4)\n",
      "测试集大小: (200, 4)\n",
      "\n",
      "==================================================\n",
      "模型评估结果\n",
      "==================================================\n",
      "R² 评分: 0.8465\n",
      "模型自带 score: 0.8465\n",
      "均方误差 (MSE): 68.10\n",
      "均方根误差 (RMSE): 8.25\n",
      "平均绝对误差 (MAE): 4.83\n",
      "\n",
      "特征重要性排序：\n",
      "     特征       重要性\n",
      "0    页数  0.487423\n",
      "1  类别编码  0.451821\n",
      "2    彩印  0.044326\n",
      "3  纸张编码  0.016430\n",
      "\n",
      "特征重要性已保存至: D:\\商业数据分析案例\\第九章\\定价模型特征重要性.xlsx\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mqq\\AppData\\Local\\Temp\\ipykernel_22860\\1434993606.py:134: UserWarning: Glyph 178 (\\N{SUPERSCRIPT TWO}) missing from current font.\n",
      "  plt.tight_layout()\n",
      "C:\\Users\\mqq\\AppData\\Local\\Temp\\ipykernel_22860\\1434993606.py:135: UserWarning: Glyph 178 (\\N{SUPERSCRIPT TWO}) missing from current font.\n",
      "  plt.savefig(r'D:\\商业数据分析案例\\第九章\\预测vs实际价格.png', dpi=300, bbox_inches='tight')\n",
      "D:\\programfiles\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 178 (\\N{SUPERSCRIPT TWO}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "预测示例（测试集前5个样本）：\n",
      "   实际价格       预测价格      绝对误差\n",
      "0    78  76.202710  1.797290\n",
      "1    66  62.398971  3.601029\n",
      "2    50  47.878207  2.121793\n",
      "3    36  40.275973  4.275973\n",
      "4    64  61.114298  2.885702\n",
      "\n",
      "平均绝对误差百分比: 7.54%\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "import numpy as np\n",
    "\n",
    "# 设置中文字体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 1. 读取数据\n",
    "df = pd.read_excel(r'D:\\商业数据分析案例\\第九章\\产品定价模型.xlsx')\n",
    "\n",
    "print(\"=\" * 50)\n",
    "print(\"GBDT产品定价模型分析\")\n",
    "print(\"=\" * 50)\n",
    "\n",
    "print(\"\\n数据基本信息：\")\n",
    "print(f\"数据形状: {df.shape}\")\n",
    "print(f\"\\n前5行数据：\")\n",
    "print(df.head())\n",
    "\n",
    "print(f\"\\n各列数据类型：\")\n",
    "print(df.dtypes)\n",
    "\n",
    "print(f\"\\n数据描述性统计：\")\n",
    "print(df.describe())\n",
    "\n",
    "# 2. 数据预处理\n",
    "print(f\"\\n类别分布：\")\n",
    "print(df['类别'].value_counts())\n",
    "\n",
    "print(f\"\\n彩印分布：\")\n",
    "print(df['彩印'].value_counts())\n",
    "\n",
    "print(f\"\\n纸张分布：\")\n",
    "print(df['纸张'].value_counts())\n",
    "\n",
    "# 对分类变量进行编码\n",
    "le_category = LabelEncoder()\n",
    "le_paper = LabelEncoder()\n",
    "\n",
    "df['类别编码'] = le_category.fit_transform(df['类别'])\n",
    "df['纸张编码'] = le_paper.fit_transform(df['纸张'])\n",
    "\n",
    "print(f\"\\n类别编码映射：\")\n",
    "for i, category in enumerate(le_category.classes_):\n",
    "    print(f\"  {category} -> {i}\")\n",
    "\n",
    "print(f\"\\n纸张编码映射：\")\n",
    "for i, paper in enumerate(le_paper.classes_):\n",
    "    print(f\"  {paper} -> {i}\")\n",
    "\n",
    "# 3. 提取特征变量和目标变量\n",
    "X = df[['页数', '类别编码', '彩印', '纸张编码']]\n",
    "y = df['价格']\n",
    "\n",
    "print(f\"\\n特征变量形状: {X.shape}\")\n",
    "print(f\"目标变量形状: {y.shape}\")\n",
    "\n",
    "# 4. 划分训练集和测试集\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "print(f\"\\n训练集大小: {X_train.shape}\")\n",
    "print(f\"测试集大小: {X_test.shape}\")\n",
    "\n",
    "# 5. 模型训练\n",
    "model = GradientBoostingRegressor(\n",
    "    n_estimators=100,\n",
    "    learning_rate=0.1,\n",
    "    max_depth=3,\n",
    "    random_state=42\n",
    ")\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "# 6. 模型预测\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "# 7. 模型评估\n",
    "r2 = r2_score(y_test, y_pred)\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "rmse = np.sqrt(mse)\n",
    "mae = mean_absolute_error(y_test, y_pred)\n",
    "score = model.score(X_test, y_test)\n",
    "\n",
    "print(\"\\n\" + \"=\" * 50)\n",
    "print(\"模型评估结果\")\n",
    "print(\"=\" * 50)\n",
    "print(f\"R² 评分: {r2:.4f}\")\n",
    "print(f\"模型自带 score: {score:.4f}\")\n",
    "print(f\"均方误差 (MSE): {mse:.2f}\")\n",
    "print(f\"均方根误差 (RMSE): {rmse:.2f}\")\n",
    "print(f\"平均绝对误差 (MAE): {mae:.2f}\")\n",
    "\n",
    "# 8. 特征重要性分析\n",
    "feature_importance = pd.DataFrame({\n",
    "    '特征': X.columns,\n",
    "    '重要性': model.feature_importances_\n",
    "}).sort_values(by='重要性', ascending=False)\n",
    "\n",
    "print(f\"\\n特征重要性排序：\")\n",
    "print(feature_importance)\n",
    "\n",
    "# 保存特征重要性结果\n",
    "feature_importance.to_excel(r'D:\\商业数据分析案例\\第九章\\定价模型特征重要性.xlsx', index=False)\n",
    "print(\"\\n特征重要性已保存至: D:\\\\商业数据分析案例\\\\第九章\\\\定价模型特征重要性.xlsx\")\n",
    "\n",
    "# 9. 可视化特征重要性（修复警告的版本）\n",
    "plt.figure(figsize=(10, 6))\n",
    "# 修复方法1：使用hue参数\n",
    "sns.barplot(data=feature_importance, x='重要性', y='特征', hue='特征', \n",
    "            palette='coolwarm', legend=False)\n",
    "plt.title('GBDT产品定价模型 - 特征重要性')\n",
    "plt.tight_layout()\n",
    "plt.savefig(r'D:\\商业数据分析案例\\第九章\\定价模型特征重要性.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "\n",
    "# 10. 预测值与真实值对比\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(y_test, y_pred, alpha=0.6)\n",
    "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'r--', lw=2)\n",
    "plt.xlabel('实际价格')\n",
    "plt.ylabel('预测价格')\n",
    "plt.title('GBDT模型预测 vs 实际价格')\n",
    "plt.grid(True, alpha=0.3)\n",
    "\n",
    "# 添加R²到图中\n",
    "plt.text(0.05, 0.95, f'R² = {r2:.4f}', transform=plt.gca().transAxes, \n",
    "         fontsize=12, verticalalignment='top', bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(r'D:\\商业数据分析案例\\第九章\\预测vs实际价格.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "\n",
    "# 11. 残差分析\n",
    "residuals = y_test - y_pred\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(y_pred, residuals, alpha=0.6)\n",
    "plt.axhline(y=0, color='red', linestyle='--')\n",
    "plt.xlabel('预测价格')\n",
    "plt.ylabel('残差')\n",
    "plt.title('残差分析图')\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.savefig(r'D:\\商业数据分析案例\\第九章\\残差分析.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "\n",
    "# 12. 误差分布\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(residuals, bins=30, alpha=0.7, color='skyblue', edgecolor='black')\n",
    "plt.xlabel('残差')\n",
    "plt.ylabel('频数')\n",
    "plt.title('残差分布')\n",
    "plt.axvline(x=0, color='red', linestyle='--', label='零误差线')\n",
    "plt.legend()\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.savefig(r'D:\\商业数据分析案例\\第九章\\残差分布.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "\n",
    "# 13. 模型预测示例\n",
    "print(f\"\\n预测示例（测试集前5个样本）：\")\n",
    "example_results = pd.DataFrame({\n",
    "    '实际价格': y_test.values[:5],\n",
    "    '预测价格': y_pred[:5],\n",
    "    '绝对误差': np.abs(y_test.values[:5] - y_pred[:5])\n",
    "})\n",
    "print(example_results)\n",
    "\n",
    "print(f\"\\n平均绝对误差百分比: {mae/y_test.mean()*100:.2f}%\")\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "colors = plt.cm.coolwarm(np.linspace(0, 1, len(feature_importance)))\n",
    "plt.barh(feature_importance['特征'], feature_importance['重要性'], color=colors)\n",
    "plt.xlabel('特征重要性')\n",
    "plt.title('GBDT产品定价模型 - 特征重要性')\n",
    "plt.tight_layout()\n",
    "plt.savefig(r'D:\\商业数据分析案例\\第九章\\定价模型特征重要性_v2.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "5a4c1ba2-1489-4ab0-a868-74571c105298",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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